Embodiments in accordance with the present invention are directed to integrated circuits and their processing for the manufacture of semiconductor devices. More particularly, embodiments in accordance with the present invention provide a method and a system for endpoint detection in an etch process. But it would be recognized that embodiments in accordance with the present invention have a much broader range of applicability.
Integrated circuits or “ICs” have evolved from a handful of interconnected devices fabricated on a single chip of silicon to millions of devices. Current ICs provide performance and complexity far beyond what was originally imagined. In order to achieve improvements in complexity and circuit density (i.e., the number of devices capable of being packed onto a given chip area), the size of the smallest device feature, also known as the device “geometry”, has become smaller with each generation of ICs. Semiconductor devices are now being fabricated with features less than a quarter of a micron across.
As merely an example, etching processes are often used to remove or partially remove a layer to form structures there from. Etching is often performed by an etching tool, such as a dry etcher or wet etcher. The wet etcher often includes a vessel that has an etchant chemical to selectively remove one material from another material. The dry etcher often includes a plasma source and treatment chamber. The dry etcher often uses gases such as fluorine bearing species and chlorine bearing species to remove semiconductor materials such as silicon, or metal such as aluminum, or dielectric material such as silicon oxide. Much work has been done to use real-time metrology to characterize semiconductor manufacturing processes and the effect of these processes on the wafers being processed. One of the big difficulties is that in contrast to ex situ metrology, which allows detailed scrutiny of the wafer surface, real-time metrology requires in situ measurement, which rarely allows such a close investigation of the wafer. Consequently, one needs to measure parameters such as the power being delivered into a process chamber, or the effluent emanating from a process chamber in order to make inferences about the state of the wafer.
Typical objectives of real-time metrology for semiconductor processes include identification of a particular wafer state, such as that point at which a particular thin film is fully etched in a plasma etch process (the end point0; or characterization of key process parameters, such as the rate at which a thin film is being deposited or etched.
One of the primary difficulties in such metrology is the correlation between the measurement and the desired objective. Changes in the measured parameter, such as effluent composition, or the voltage associated with the power being delivered into the process chamber, depend on a myriad different process, chamber, and/or wafer parameters. For example, the amount of effluent being measured depends on whether or not one has completely etched though a particular film, but it will also depend on the temperature of the wafer, the rate at which gases are flowing into the chamber, the power being delivered, and many other parameters.
Currently, this problem is being addressed by running the process under different conditions, either with a design of experiments or with the natural variations that occur in a manufacturing environment, and using techniques such as neural network analysis to find those correlations between the measured parameters and the desired objective such that one can depend on the correlation across a variety of process conditions. Unfortunately, such an approach is not highly robust.
Other conventional techniques such as optical emission spectroscopy (OES) or radio frequency (RF) measurement are also used to determine when a target layer is completely removed or endpoint of the etch process. However as device shrinks, the area of the material removed is a very small fraction of the overall area. In a typical via etch, for example, the area of dielectric layer to be removed is only about 1% or less of the total area. Since OES or RF measurements measure an overall plasma state, the effect from other interferences often overwhelms the signal of the measurement. In addition, conventional endpoint detection relies on mathematic techniques such as multivariate analysis or neural networks to identify the endpoint signal. In absence of physical understanding of factors affecting the signal of measurement, the problem of looking at a wrong signal is further exacerbated. This leads to an over etch or an under etch of the material and impact device performance.
From the above, it is seen that an improved technique for processing semiconductor devices is desired